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DILAF: A framework for distributed analysis of large-scale system logs for anomaly detection
(Wiley, 2019-02)
System logs constitute a rich source of information for detection and prediction of anomalies. However, they can include a huge volume of data, which is usually unstructured or semistructured. We introduce DILAF, a framework ...
Evaluation of distributed machine learning algorithms for anomaly detection from large-scale system logs: a case study
(IEEE, 2018)
Anomaly detection is a valuable feature for detecting and diagnosing faults in large-scale, distributed systems. These systems usually provide tens of millions of lines of logs that can be exploited for this purpose. ...
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